Survey on Endoparasites of Dairy Goats in North-Eastern Italy Using a Farm-Tailored Monitoring Approach

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Maurizio A., Stancampiano L., Tessarin C., Pertile A., Pedrini G., Asti C., ...Daha Fazla

VETERINARY SCIENCES, cilt.8, sa.5, 2021 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 5
  • Basım Tarihi: 2021
  • Doi Numarası: 10.3390/vetsci8050069
  • Dergi Adı: VETERINARY SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, EMBASE, Veterinary Science Database, Directory of Open Access Journals
  • Anahtar Kelimeler: dairy goats, endoparasites, Italy, sample size, aggregation, GASTROINTESTINAL PARASITIC INFECTIONS, TARGETED SELECTIVE TREATMENTS, EYE COLOR CHART, RISK-FACTORS, ANTHELMINTIC RESISTANCE, NEMATODE INFECTIONS, CLINICAL ANEMIA, MILK-PRODUCTION, 1ST REPORT, EGG COUNT
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Ankara Üniversitesi Adresli: Evet

Özet

With the spread of anthelmintic resistance (AR), endoparasite monitoring consolidates its role for a more sustainable targeting of treatments. A survey on endoparasites in dairy goat farms of north-eastern Italy was conducted to test a monitoring approach based on a farm-tailored sample size. Farm management and parasites control practices were investigated in 20 farms through a questionnaire survey. Further, fecal samples were collected (November 2018-September 2019) from 264 animals from 13 farms and were analyzed individually with a modified McMaster method and subsequently pooled to perform a coproculture. Coccidia (78.4%), gastrointestinal strongyles (37.9%), Strongyloides (28.4%), Skrjabinema (18.9%), Trichuris (8.0%) and Nematodirus/Marshallagia (0.4%) were identified. Abundances were higher for coccidia and gastrointestinal strongyles. Haemonchus (71%) was the dominant gastrointestinal nematode. Pasture and age class resulted in the main risk factors at the multivariable analysis through a negative binomial regression model. Results from farm monitoring indicate that our approach can be a cost-effective decision tool to target treatments more effectively, but farmers need to be educated about the importance of parasitological testing, which is currently scarcely implemented, against the risk of AR.